1r.surf.idw(1) Grass User's Manual r.surf.idw(1)
2
6 r.surf.idw - Surface interpolation utility for raster map layers.
7
9 raster
10
12 r.surf.idw
13 r.surf.idw help
14 r.surf.idw [-e] input=name output=name [npoints=integer] [--over‐
15 write] [--verbose] [--quiet]
16 Flags:
18 -e
19 Output is the interpolation error
20 --overwrite
22 Allow output files to overwrite existing files
23 --verbose
25 Verbose module output
26 --quiet
28 Quiet module output
29 Parameters:
31 input=name
32 Name of input raster map
33 output=name
35 Name for output raster map
36 npoints=integer
38 Number of interpolation points
39 Default: 12
40
42 r.surf.idw fills a grid cell (raster) matrix with interpolated values
43 generated from a set of input layer data points. It uses a numerical
44 approximation technique based on distance squared weighting of the val‐
45 ues of nearest data points. The number of nearest data points used to
46 determined the interpolated value of a cell can be specified by the
47 user (default: 12 nearest data points).
48 If there is a current working mask, it applies to the output raster
50 map. Only those cells falling within the mask will be assigned interpo‐
51 lated values. The search procedure for the selection of nearest neigh‐
52 boring points will consider all input data, without regard to the mask.
53 The -e flag is the error analysis option that interpolates values only
54 for those cells of the input raster map which have non-zero values and
55 outputs the difference (see NOTES below).
56 The npoints parameter defines the number of nearest data points used to
58 determine the interpolated value of an output raster cell.
59
61 r.surf.idw is a surface generation utility which uses inverse distance
62 squared weighting (as described in Applied Geostatistics by E. H.
63 Isaaks and R. M. Srivastava, Oxford University Press, 1989) to assign
64 interpolated values. The implementation includes a customized data
65 structure somewhat akin to a sparse matrix which enhances the effi‐
66 ciency with which nearest data points are selected. For latitude/lon‐
67 gitude projections, distances are calculated from point to point along
68 a geodesic.
69 Unlike r.surf.idw2, which processes all input data points in each
71 interpolation cycle, r.surf.idw attempts to minimize the number of
72 input data for which distances must be calculated. Execution speed is
73 therefore a function of the search effort, and does not increase appre‐
74 ciably with the number of input data points.
75 r.surf.idw will generally outperform <A
77 HREF="r.surf.idw2.html">r.surf.idw2 except when the input data layer
78 contains few non-zero data, i.e. when the cost of the search exceeds
79 the cost of the additional distance calculations performed by <A
80 HREF="r.surf.idw2.html">r.surf.idw2. The relative performance of these
81 utilities will depend on the comparative speed of boolean, integer and
82 floating point operations on a particular platform.
83 Worst case search performance by r.surf.idw occurs when the interpo‐
85 lated cell is located outside of the region in which input data are
86 distributed. It therefore behooves the user to employ a mask when geo‐
87 graphic region boundaries include large areas outside the general
88 extent of the input data.
89 The degree of smoothing produced by the interpolation will increase
91 relative to the number of nearest data points considered. The utility
92 may be used with regularly or irregularly spaced input data. However,
93 the output result for the former may include unacceptable nonconformi‐
94 ties in the surface pattern.
95 The -e flag option provides a standard surface-generation error analy‐
97 sis facility. It produces an output raster map of the difference of
98 interpolated values minus input values for those cells whose input data
99 are non-zero. For each interpolation cycle, the known value of the cell
100 under consideration is ignored, and the remaining input values are used
101 to interpolate a result. The output raster map may be compared to the
102 input raster map to analyze the distribution of interpolation error.
103 This procedure may be helpful in choosing the number of nearest neigh‐
104 bors considered for surface generation.
105
107 r.surf.contour, r.surf.idw2, r.surf.gauss, r.surf.fractal, r.surf.ran‐
108 dom, v.surf.idw, v.surf.rst
109
111 Greg Koerper
112 Global Climate Research Project
113 U.S. EPA Environmental Research Laboratory
114 200 S.W. 35th Street, JSB
115 Corvallis, OR 97333
116 Last changed: $Date: 2006-12-13 15:21:43 +0100 (Wed, 13 Dec 2006) $
118 Full index
120 © 2003-2008 GRASS Development Team
122GRASS 6.3.0 r.surf.idw(1)